In its recent report on "Yelp's Rocky Relationship with Small Businesses," PBS Media Shift was the latest mainstream media outlet to cover one of the most controversial topics in all of local search: search engines' filtering of customer reviews.

The topic first came to prominence four years ago in Kathleen Richards' landmark piece on Yelp's aggressive sales pitches — or extortion, depending on your perspective and whom you believe. While I was never fully convinced of corporate misbehavior on Yelp's part, the company hasn't done itself any favors by continuing to allow its field operatives to use deceptive sales tactics. Despite its best efforts to educate both business owners and everyday users of the site, the poor reputation of Yelp's salespeople continues to contribute to confusion around review filtering among the small business community. I hope to be able to clear up some of that confusion with this post and offer a few tactical tips to help avoid the frustration these filters can cause.

Why review filters exist

As local search usage among the general public has exploded over the last several years, more and more directories have (rightly) seen reviews as a way to:

Gauge the offline popularity of a business in their algorithms

Provide better insight to searchers into the experience at that business

Increase the "stickiness" of their sites by increasing the sense of community

Get out of Google's Panda/Farmer purgatory by adding unique user content

In many ways, Yelp was ahead of its time on all four of these bullet points, and as a result, it had to tackle the inevitable review spam that accompanied its popularity.

Its answer was arguably the first widespread local review filter: an algorithm for detecting and removing spam or suspicious-looking content. In Yelp's own words:

For those of you who couldn't quite keep up with Yelp's version of Micro Machines man, the primary reasons are:

To make sure reviews are left by actual people (not robots)

To make sure reviews are left by customers and not just hired third parties

To make sure businesses don't leave reviews of themselves

Yelp's CEO, Jeremy Stoppelman, recently gave his own slower version of this rationale in a company-produced video:

How review filters work

While I don't have any detailed knowledge of Yelp's review filter specifically, many comparable filters seem to kick into action if any of the following is present in the content of the review:

Use of extreme adjectives or profanity in the review

Over-use of keywords in the review

Inclusion of links in the review

Another criterion that also tends to trigger filtering is a sudden burst of reviews preceded by or followed by a long lull between them.

Some of the more sophisticated review filters, including Yelp's, take a look at user characteristics, too, including:

Total number of reviews a user has left on the site

Distribution of ratings across all of a user's reviews

Distribution of business types among all of a user's reviews

Frequency of reviews that a user has left on the site

IP address(es) of the user when leaving reviews

The bottom line is that reviews written by active users have an astronomically-higher likelihood of "sticking" on a local search engine than those written by first-time or infrequent reviewers. And even beyond their stickiness, many local search experts (including myself) speculate that reviews left by active users also influence rankings to a much greater extent than those left by first-time or infrequent reviewers.

The algorithms behind review filters are far from perfect, as many readers probably know, and Yelp is far from the only local search engine with a review filter. In fact, Google+ has probably accrued more ire from business owners as a result of its filter in 2012 and 2013 than any other site.

All of which leads to frustration from the standpoint of a small business owner.

Avoiding review filters

Yelp is probably the most aggressive of its peers at enforcing its business review guidelines, which also happen to be the most onerous guidelines of any local search engine. Yelp's filtering is so aggressive that one in five reviews written on Yelp never shows up on the site!

To sum up those guidelines:

Don't ask anyone to review your business on Yelp.

Don't ask anyone to review your business on Yelp.

Don't ask anyone to review your business on Yelp.

O ye business owner who disobeys those guidelines, beware! You run the risk of a public shaming.

The review filters of the future

The primary methods of these filters, though, I think will change pretty dramatically. Rather than judging a review by its content or looking at website behavior (e.g. how many reviews a user has left for other businesses), the explosion in smartphone adoption is enabling a couple of far less easily-manipulated criteria to judge the veracity of a review.

Any local search platform operated by a handset maker (Google, Apple, Microsoft, Nokia, …Amazon?) could register the device ID at the time of review and tie it to a bonafide human being.

Any local search platform that has implemented mobile payment processing (Google, Apple, …Amazon?, any Square/PayPalHere partner) could disable the ability for a user to leave a review of a retail-category business unless he/she had completed a transaction at the storefront.

And even for those platforms without the handset or payment-processing advantage, requiring location-awareness for users of mobile applications prior to leaving a review seems like a no-brainer (which Yelp has already implemented and Google may be well on its way to doing).

For those sites that are more desktop-dependent, widespread adoption of primary social logins (Google+, Facebook, Twitter, etc.) could lead to a baked-in layer of spam-fighting.

“Within search results, information tied to verified online profiles will be ranked higher than content without such verification, which will result in most users naturally clicking on the top (verified) results. The true cost of remaining anonymous, then, might be irrelevance.”

In some industries (e.g., DUI law, plastic surgery, psychology), anonymity may be a pre-requisite for any user reviews and these local search platforms may need a Plan B. But for most industries, requiring some sort of verified social profile would solve a lot of problems.

Facebook, of course, has a huge leg up on everyone else based on its knowledge of a user's social connections. Google+, meanwhile, could look at a user's activity across Google's entire range of products (web search, Gmail, YouTube, etc.) to stop spammers in their tracks.

While consumer privacy concerns around these mechanisms for review filtering may arise, many business owners would likely rejoice at a truer, less bug-ridden filtering algorithm and a more accurate and complete representation of their customers' experience.

Well, that's enough out of me for this week! How about you? What are some of your strategies for avoiding these dreaded review filters? What other methods of filtering do you see coming to Local Search?

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